C++ PetscTryMethod函数代码示例

/*@
    TSPseudoSetMaxTimeStep - Sets the maximum time step
    when using the TSPseudoTimeStepDefault() routine.

   Logically Collective on TS

    Input Parameters:
+   ts - the timestep context
-   maxdt - the maximum time step, use a non-positive value to deactivate

    Options Database Key:
$    -ts_pseudo_max_dt <increment>

    Level: advanced

.keywords: timestep, pseudo, set

.seealso: TSPseudoSetTimeStep(), TSPseudoTimeStepDefault()
@*/
PetscErrorCode  TSPseudoSetMaxTimeStep(TS ts,PetscReal maxdt)
{
  PetscErrorCode ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(ts,TS_CLASSID,1);
  PetscValidLogicalCollectiveReal(ts,maxdt,2);
  ierr = PetscTryMethod(ts,"TSPseudoSetMaxTimeStep_C",(TS,PetscReal),(ts,maxdt));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@
   EPSJDSetKrylovStart - Activates or deactivates starting the searching
   subspace with a Krylov basis.

   Logically Collective on EPS

   Input Parameters:
+  eps - the eigenproblem solver context
-  krylovstart - boolean flag

   Options Database Key:
.  -eps_jd_krylov_start - Activates starting the searching subspace with a
    Krylov basis

   Level: advanced

.seealso: EPSJDGetKrylovStart()
@*/
PetscErrorCode EPSJDSetKrylovStart(EPS eps,PetscBool krylovstart)
{
  PetscErrorCode ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(eps,EPS_CLASSID,1);
  PetscValidLogicalCollectiveBool(eps,krylovstart,2);
  ierr = PetscTryMethod(eps,"EPSJDSetKrylovStart_C",(EPS,PetscBool),(eps,krylovstart));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@
   MatPartitioningChacoSetEigenTol - Sets the tolerance for the eigensolver.

   Collective on MatPartitioning

   Input Parameters:
+  part - the partitioning context
-  tol  - the tolerance

   Options Database:
.  -mat_partitioning_chaco_eigen_tol <tol>: Tolerance for eigensolver

   Note:
   Must be positive. The default value is 0.001.

   Level: advanced

.seealso: MatPartitioningChacoSetEigenSolver(), MatPartitioningChacoGetEigenTol()
@*/
PetscErrorCode MatPartitioningChacoSetEigenTol(MatPartitioning part,PetscReal tol)
{
  PetscErrorCode ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(part,MAT_PARTITIONING_CLASSID,1);
  PetscValidLogicalCollectiveReal(part,tol,2);
  ierr = PetscTryMethod(part,"MatPartitioningChacoSetEigenTol_C",(MatPartitioning,PetscReal),(part,tol));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@
   PCRedundantSetNumber - Sets the number of redundant preconditioner contexts.

   Logically Collective on PC

   Input Parameters:
+  pc - the preconditioner context
-  nredundant - number of redundant preconditioner contexts; for example if you are using 64 MPI processes and
                              use an nredundant of 4 there will be 4 parallel solves each on 16 = 64/4 processes.

   Level: advanced

.keywords: PC, redundant solve
@*/
PetscErrorCode PCRedundantSetNumber(PC pc,PetscInt nredundant)
{
  PetscErrorCode ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(pc,PC_CLASSID,1);
  if (nredundant <= 0) SETERRQ1(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONG, "num of redundant pc %D must be positive",nredundant);
  ierr = PetscTryMethod(pc,"PCRedundantSetNumber_C",(PC,PetscInt),(pc,nredundant));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@C
     PetscViewerFileSetMode - Sets the type of file to be open

    Logically Collective on PetscViewer

  Input Parameters:
+  viewer - the PetscViewer; must be a binary, Matlab, hdf, or netcdf PetscViewer
-  type - type of file
$    FILE_MODE_WRITE - create new file for binary output
$    FILE_MODE_READ - open existing file for binary input
$    FILE_MODE_APPEND - open existing file for binary output

  Level: advanced

.seealso: PetscViewerFileSetMode(), PetscViewerCreate(), PetscViewerSetType(), PetscViewerBinaryOpen()

@*/
PetscErrorCode  PetscViewerFileSetMode(PetscViewer viewer,PetscFileMode type)
{
  PetscErrorCode ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,1);
  PetscValidLogicalCollectiveEnum(viewer,type,2);
  ierr = PetscTryMethod(viewer,"PetscViewerFileSetMode_C",(PetscViewer,PetscFileMode),(viewer,type));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@
   PEPLinearSetExplicitMatrix - Indicate if the matrices A and B for the
   linearization of the problem must be built explicitly.

   Logically Collective on PEP

   Input Parameters:
+  pep      - polynomial eigenvalue solver
-  explicit - boolean flag indicating if the matrices are built explicitly

   Options Database Key:
.  -pep_linear_explicitmatrix <boolean> - Indicates the boolean flag

   Level: advanced

.seealso: PEPLinearGetExplicitMatrix()
@*/
PetscErrorCode PEPLinearSetExplicitMatrix(PEP pep,PetscBool explicitmatrix)
{
  PetscErrorCode ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(pep,PEP_CLASSID,1);
  PetscValidLogicalCollectiveBool(pep,explicitmatrix,2);
  ierr = PetscTryMethod(pep,"PEPLinearSetExplicitMatrix_C",(PEP,PetscBool),(pep,explicitmatrix));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@
   SVDTRLanczosSetOneSide - Indicate if the variant of the Lanczos method
   to be used is one-sided or two-sided.

   Logically Collective on SVD

   Input Parameters:
+  svd     - singular value solver
-  oneside - boolean flag indicating if the method is one-sided or not

   Options Database Key:
.  -svd_trlanczos_oneside <boolean> - Indicates the boolean flag

   Note:
   By default, a two-sided variant is selected, which is sometimes slightly
   more robust. However, the one-sided variant is faster because it avoids
   the orthogonalization associated to left singular vectors.

   Level: advanced

.seealso: SVDLanczosSetOneSide()
@*/
PetscErrorCode SVDTRLanczosSetOneSide(SVD svd,PetscBool oneside)
{
  PetscErrorCode ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(svd,SVD_CLASSID,1);
  PetscValidLogicalCollectiveBool(svd,oneside,2);
  ierr = PetscTryMethod(svd,"SVDTRLanczosSetOneSide_C",(SVD,PetscBool),(svd,oneside));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@
    KSPCGUseSingleReduction - Merge the two inner products needed in CG into a single MPI_Allreduce() call.

    Logically Collective on KSP

    Input Parameters:
+   ksp - the iterative context
-   flg - turn on or off the single reduction

    Options Database:
.   -ksp_cg_single_reduction 

    Level: intermediate

     The algorithm used in this case is described as Method 1 in Lapack Working Note 56, "Conjugate Gradient Algorithms with Reduced Synchronization Overhead 
     Distributed Memory Multiprocessors", by E. F. D'Azevedo, V. L. Eijkhout, and C. H. Romine, December 3, 1999. V. Eijkhout creates the algorithm 
     initially to Chronopoulos and Gear.

     It requires two extra work vectors than the conventional implementation in PETSc. 
    
.keywords: CG, conjugate gradient, Hermitian, symmetric, set, type
@*/
PetscErrorCode  KSPCGUseSingleReduction(KSP ksp,PetscBool  flg)
{
  PetscErrorCode ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(ksp,KSP_CLASSID,1);
  PetscValidLogicalCollectiveBool(ksp,flg,2);
  ierr = PetscTryMethod(ksp,"KSPCGUseSingleReduction_C",(KSP,PetscBool),(ksp,flg));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@C
   SNESCompositeSetType - Sets the type of composite preconditioner.

   Logically Collective on SNES

   Input Parameter:
+  snes - the preconditioner context
-  type - SNES_COMPOSITE_ADDITIVE (default), SNES_COMPOSITE_MULTIPLICATIVE

   Options Database Key:
.  -snes_composite_type <type: one of multiplicative, additive, special> - Sets composite preconditioner type

   Level: Developer

.keywords: SNES, set, type, composite preconditioner, additive, multiplicative
@*/
PetscErrorCode  SNESCompositeSetType(SNES snes,SNESCompositeType type)
{
  PetscErrorCode ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(snes,SNES_CLASSID,1);
  PetscValidLogicalCollectiveEnum(snes,type,2);
  ierr = PetscTryMethod(snes,"SNESCompositeSetType_C",(SNES,SNESCompositeType),(snes,type));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@
    KSPQCGSetTrustRegionRadius - Sets the radius of the trust region.

    Logically Collective on KSP

    Input Parameters:
+   ksp   - the iterative context
-   delta - the trust region radius (Infinity is the default)

    Options Database Key:
.   -ksp_qcg_trustregionradius <delta>

    Level: advanced

.keywords: KSP, QCG, set, trust region radius
@*/
PetscErrorCode  KSPQCGSetTrustRegionRadius(KSP ksp,PetscReal delta)
{
  PetscErrorCode ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(ksp,KSP_CLASSID,1);
  if (delta < 0.0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Tolerance must be non-negative");
  ierr = PetscTryMethod(ksp,"KSPQCGSetTrustRegionRadius_C",(KSP,PetscReal),(ksp,delta));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@
   KSPChebyshevEstEigSetRandom - set random context for estimating eigenvalues

   Logically Collective

   Input Arguments:
+  ksp - linear solver context
-  random - random number context or NULL to use default

  Level: intermediate

.seealso: KSPChebyshevEstEigSet(), PetscRandomCreate()
@*/
PetscErrorCode KSPChebyshevEstEigSetRandom(KSP ksp,PetscRandom random)
{
  PetscErrorCode ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(ksp,KSP_CLASSID,1);
  if (random) PetscValidHeaderSpecific(random,PETSC_RANDOM_CLASSID,2);
  ierr = PetscTryMethod(ksp,"KSPChebyshevEstEigSetRandom_C",(KSP,PetscRandom),(ksp,random));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@
  SNESMultiblockSetBlockSize - Sets the block size for structured mesh block division. If not set the matrix block size is used.

  Logically Collective on SNES

  Input Parameters:
+ snes - the solver context
- bs   - the block size

  Level: intermediate

.seealso: SNESMultiblockGetSubSNES(), SNESMULTIBLOCK, SNESMultiblockSetFields()
@*/
PetscErrorCode SNESMultiblockSetBlockSize(SNES snes, PetscInt bs)
{
  PetscErrorCode ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(snes, SNES_CLASSID, 1);
  PetscValidLogicalCollectiveInt(snes, bs, 2);
  ierr = PetscTryMethod(snes, "SNESMultiblockSetBlockSize_C", (SNES, PetscInt), (snes,bs));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@
   PCFactorSetShiftType - adds a particular type of quantity to the diagonal of the matrix during
     numerical factorization, thus the matrix has nonzero pivots

   Logically Collective on PC

   Input Parameters:
+  pc - the preconditioner context
-  shifttype - type of shift; one of MAT_SHIFT_NONE, MAT_SHIFT_NONZERO,  MAT_SHIFT_POSITIVE_DEFINITE, MAT_SHIFT_INBLOCKS

   Options Database Key:
.  -pc_factor_shift_type <shifttype> - Sets shift type or PETSC_DECIDE for the default; use '-help' for a list of available types

   Level: intermediate

.keywords: PC, set, factorization,

.seealso: PCFactorSetZeroPivot(), PCFactorSetShiftAmount()
@*/
PetscErrorCode  PCFactorSetShiftType(PC pc,MatFactorShiftType shifttype)
{
  PetscErrorCode ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(pc,PC_CLASSID,1);
  PetscValidLogicalCollectiveEnum(pc,shifttype,2);
  ierr = PetscTryMethod(pc,"PCFactorSetShiftType_C",(PC,MatFactorShiftType),(pc,shifttype));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@
   MatPartitioningPartySetBipart - Activate or deactivate recursive bisection.

   Collective on MatPartitioning

   Input Parameters:
+  part - the partitioning context
-  bp - boolean flag

   Options Database:
-  -mat_partitioning_party_bipart - Bipartitioning option on/off

   Level: advanced
@*/
PetscErrorCode MatPartitioningPartySetBipart(MatPartitioning part,PetscBool bp)
{
  PetscErrorCode ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(part,MAT_PARTITIONING_CLASSID,1);
  PetscValidLogicalCollectiveBool(part,bp,2);
  ierr = PetscTryMethod(part,"MatPartitioningPartySetBipart_C",(MatPartitioning,PetscBool),(part,bp));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*@
   PCCompositeSpecialSetAlpha - Sets alpha for the special composite preconditioner
     for alphaI + R + S

   Logically Collective on PC

   Input Parameter:
+  pc - the preconditioner context
-  alpha - scale on identity

   Level: Developer

.keywords: PC, set, type, composite preconditioner, additive, multiplicative
@*/
PetscErrorCode  PCCompositeSpecialSetAlpha(PC pc,PetscScalar alpha)
{
  PetscErrorCode ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(pc,PC_CLASSID,1);
  PetscValidLogicalCollectiveScalar(pc,alpha,2);
  ierr = PetscTryMethod(pc,"PCCompositeSpecialSetAlpha_C",(PC,PetscScalar),(pc,alpha));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}